Arrow
Arrow
is rapidly becoming the de facto standard for columnar data. This means that
support for Arrow
is growing rapidly (both languages and tools). Due to the amazing
effort behind the format, using Arrow
is now likely the fastest way to:
- Read and write
Parquet
formatted files - Read CSV into columnar data
- Exchanging columnar data
Polars
uses an Arrow
memory buffer as the most basic building block for the Polars
Series
. This means that we exchange data between Polars
and Arrow
without
copying it. It also means that Polars
shares the same performance gains that Arrow
receives.
Convert a Polars
DataFrame
or Series
to Arrow
using the .to_arrow()
method. Similarly, importing from Arrow
data structure can be performed with the
.from_arrow()
functions.